snapshot...

modules/deeplearning/unet.py

@@ -199,8 +199,8 @@ class UNET:
         data = data.astype(np.float32)
         label = label.astype(np.float32)
 
-        data = scale(data, param, None)
-        label = scale(label, param, None)
+        data = normalize(data, param, mean_std_dct)
+        label = normalize(label, param, mean_std_dct)
 
         if is_training and DO_AUGMENT:
             data_ud = np.flip(data, axis=1)